Graph embedding on mass spectrometry- and sequencing-based biomedical data.

Graph embedding techniques are using deep learning algorithms in data analysis to solve problems of such as node classification, link prediction, community detection, and visualization. Although typically used in the context of guessing friendships in social media, several applications for graph embedding techniques in biomedical data analysis have emerged. While these approaches remain computationally demanding, several developments over the last years facilitate their application to study biomedical data and thus may help advance biological discoveries. Therefore, in this review, we discuss the principles of graph embedding techniques and explore the usefulness for understanding biological network data derived from mass spectrometry and sequencing experiments, the current workhorses of systems biology studies. In particular, we focus on recent examples for characterizing protein-protein interaction networks and predicting novel drug functions.

Reversible amyloids of pyruvate kinase couple cell metabolism and stress granule disassembly.

Cells respond to stress by blocking translation, rewiring metabolism and forming transient messenger ribonucleoprotein assemblies called stress granules (SGs). After stress release, re-establishing homeostasis and disassembling SGs requires ATP-consuming processes. However, the molecular mechanisms whereby cells restore ATP production and disassemble SGs after stress remain poorly understood. Here we show that upon stress, the ATP-producing enzyme Cdc19 forms inactive amyloids, and that their rapid re-solubilization is essential to restore ATP production and disassemble SGs in glucose-containing media. Cdc19 re-solubilization is initiated by the glycolytic metabolite fructose-1,6-bisphosphate, which directly binds Cdc19 amyloids, allowing Hsp104 and Ssa2 chaperone recruitment and aggregate re-solubilization. Fructose-1,6-bisphosphate then promotes Cdc19 tetramerization, which boosts its activity to further enhance ATP production and SG disassembly. Together, these results describe a molecular mechanism that is critical for stress recovery and directly couples cellular metabolism with SG dynamics via the regulation of reversible Cdc19 amyloids.

High-throughput multiparametric imaging flow cytometry: toward diffraction-limited sub-cellular detection and monitoring of sub-cellular processes.

We present a sheathless, microfluidic imaging flow cytometer that incorporates stroboscopic illumination for blur-free fluorescence detection at ultra-high analytical throughput. The imaging platform is capable of multiparametric fluorescence quantification and sub-cellular localization of these structures down to 500 nm with microscopy image quality. We demonstrate the efficacy of the approach through the analysis and localization of P-bodies and stress granules in yeast and human cells using fluorescence and bright-field detection at analytical throughputs in excess of 60,000 and 400,000 cells/s, respectively. Results highlight the utility of our imaging flow cytometer in directly investigating phase-separated compartments within cellular environments and screening rare events at the sub-cellular level for a range of diagnostic applications.

Cytosolic pH regulates proliferation and tumour growth by promoting expression of cyclin D1.

Enhanced growth and proliferation of cancer cells are accompanied by profound changes in cellular metabolism. These metabolic changes are also common under physiological conditions, and include increased glucose fermentation accompanied by elevated cytosolic pH (pHc)1,2. However, how these changes contribute to enhanced cell growth and proliferation is unclear. Here, we show that elevated pHc specifically orchestrates an E2F-dependent transcriptional programme to drive cell proliferation by promoting cyclin D1 expression. pHc-dependent transcription of cyclin D1 requires the transcription factors CREB1, ATF1 and ETS1, and the histone acetyltransferases p300 and CBP. Biochemical characterization revealed that the CREB1-p300/CBP interaction acts as a pH sensor and coincidence detector, integrating different mitotic signals to regulate cyclin D1 transcription. We also show that elevated pHc contributes to increased cyclin D1 expression in malignant pleural mesotheliomas (MPMs), and renders these cells hypersensitive to pharmacological reduction of pHc. Taken together, these data demonstrate that elevated pHc is a critical cellular signal regulating G1 progression, and provide a mechanism linking elevated pHc to oncogenic activation of cyclin D1 in MPMs, and possibly other cyclin D1~dependent tumours. Thus, an increase of pHc may represent a functionally important, early event in the aetiology of cancer that is amenable to therapeutic intervention.

Another Consequence of the Warburg Effect? Metabolic Regulation of Na+/H+ Exchangers May Link Aerobic Glycolysis to Cell Growth.

To adjust cell growth and proliferation to changing environmental conditions or developmental requirements, cells have evolved a remarkable network of signaling cascades that integrates cues from cellular metabolism, growth factor availability and a large variety of stresses. In these networks, cellular information flow is mostly mediated by posttranslational modifications, most notably phosphorylation, or signaling molecules such as GTPases. Yet, a large body of evidence also implicates cytosolic pH (pHc) as a highly conserved cellular signal driving cell growth and proliferation, suggesting that pH-dependent protonation of specific proteins also regulates cellular signaling. In mammalian cells, pHc is regulated by growth factor derived signals and responds to metabolic cues in response to glucose stimulation. Importantly, high pHc has also been identified as a hall mark of cancer, but mechanisms of pH regulation in cancer are only poorly understood. Here, we discuss potential mechanisms of pH regulation with emphasis on metabolic signals regulating pHc by Na+/H+-exchangers. We hypothesize that elevated NHE activity and pHc in cancer are a direct consequence of the metabolic adaptations in tumor cells including enhanced aerobic glycolysis, generally referred to as the Warburg effect. This hypothesis not only provides an explanation for the growth advantage conferred by a switch to aerobic glycolysis beyond providing precursors for accumulation of biomass, but also suggests that treatments targeting pH regulation as a potential anti-cancer therapy may effectively target the result of altered tumor cell metabolism.

Reversible, functional amyloids: towards an understanding of their regulation in yeast and humans.

Protein aggregates, and in particular amyloids, are generally considered to be inherently irreversible aberrant clumps, and are often associated with pathologies, such as Alzheimer's disease, Parkinson's disease, or systemic amyloidosis. However, recent evidence demonstrates that some aggregates are not only fully reversible, but also perform essential physiological functions. Despite these new findings, very little is known about how these functional protein aggregates are regulated in a physiological context. Here, we take the yeast pyruvate kinase Cdc19 as an example of a protein forming functional, reversible, solid, amyloid-like aggregates in response to stress conditions. Cdc19 aggregation is regulated via an aggregation-prone low complexity region (LCR). In favorable growth conditions, this LCR is prevented from aggregating by phosphorylation or oligomerization, while upon glucose starvation it becomes exposed and allows aggregation. We suggest that LCR phosphorylation, oligomerization or partner-binding may be general and widespread mechanisms regulating LCR-mediated reversible protein aggregation. Moreover, we show that, as predicted by computational tools, Cdc19 forms amyloid-like aggregates in vitro. Interestingly, we also observe striking similarities between Cdc19 and its mammalian counterpart, PKM2. Indeed, also PKM2 harbors a LCR and contains several peptides with high amyloidogenic propensity, which coincide with known phosphorylation sites. Thus, we speculate that the formation of reversible, amyloid-like aggregates may be a general physiological mechanism for cells to adapt to stress conditions, and that the underlying regulatory mechanisms may be conserved from yeast to humans.

Protein kinase C and calcineurin cooperatively mediate cell survival under compressive mechanical stress.

Cells experience compressive stress while growing in limited space or migrating through narrow constrictions. To survive such stress, cells reprogram their intracellular organization to acquire appropriate mechanical properties. However, the mechanosensors and downstream signaling networks mediating these changes remain largely unknown. Here, we have established a microfluidic platform to specifically trigger compressive stress, and to quantitatively monitor single-cell responses of budding yeast in situ. We found that yeast senses compressive stress via the cell surface protein Mid2 and the calcium channel proteins Mid1 and Cch1, which then activate the Pkc1/Mpk1 MAP kinase pathway and calcium signaling, respectively. Genetic analysis revealed that these pathways work in parallel to mediate cell survival. Mid2 contains a short intracellular tail and a serine-threonine-rich extracellular domain with spring-like properties, and both domains are required for mechanosignaling. Mid2-dependent spatial activation of the Pkc1/Mpk1 pathway depolarizes the actin cytoskeleton in budding or shmooing cells, thereby antagonizing polarized growth to protect cells under compressive stress conditions. Together, these results identify a conserved signaling network responding to compressive mechanical stress, which, in higher eukaryotes, may ensure cell survival in confined environments.

Reversible protein aggregation is a protective mechanism to ensure cell cycle restart after stress.

Protein aggregation is mostly viewed as deleterious and irreversible causing several pathologies. However, reversible protein aggregation has recently emerged as a novel concept for cellular regulation. Here, we characterize stress-induced, reversible aggregation of yeast pyruvate kinase, Cdc19. Aggregation of Cdc19 is regulated by oligomerization and binding to allosteric regulators. We identify a region of low compositional complexity (LCR) within Cdc19 as necessary and sufficient for reversible aggregation. During exponential growth, shielding the LCR within tetrameric Cdc19 or phosphorylation of the LCR prevents unscheduled aggregation, while its dephosphorylation is necessary for reversible aggregation during stress. Cdc19 aggregation triggers its localization to stress granules and modulates their formation and dissolution. Reversible aggregation protects Cdc19 from stress-induced degradation, thereby allowing cell cycle restart after stress. Several other enzymes necessary for G1 progression also contain LCRs and aggregate reversibly during stress, implying that reversible aggregation represents a conserved mechanism regulating cell growth and survival.

Inferring causal metabolic signals that regulate the dynamic TORC1-dependent transcriptome.

Cells react to nutritional cues in changing environments via the integrated action of signaling, transcriptional, and metabolic networks. Mechanistic insight into signaling processes is often complicated because ubiquitous feedback loops obscure causal relationships. Consequently, the endogenous inputs of many nutrient signaling pathways remain unknown. Recent advances for system-wide experimental data generation have facilitated the quantification of signaling systems, but the integration of multi-level dynamic data remains challenging. Here, we co-designed dynamic experiments and a probabilistic, model-based method to infer causal relationships between metabolism, signaling, and gene regulation. We analyzed the dynamic regulation of nitrogen metabolism by the target of rapamycin complex 1 (TORC1) pathway in budding yeast. Dynamic transcriptomic, proteomic, and metabolomic measurements along shifts in nitrogen quality yielded a consistent dataset that demonstrated extensive re-wiring of cellular networks during adaptation. Our inference method identified putative downstream targets of TORC1 and putative metabolic inputs of TORC1, including the hypothesized glutamine signal. The work provides a basis for further mechanistic studies of nitrogen metabolism and a general computational framework to study cellular processes.

Cytosolic pH regulates cell growth through distinct GTPases, Arf1 and Gtr1, to promote Ras/PKA and TORC1 activity.

Regulation of cell growth by nutrients is governed by highly conserved signaling pathways, yet mechanisms of nutrient sensing are still poorly understood. In yeast, glucose activates both the Ras/PKA pathway and TORC1, which coordinately regulate growth through enhancing translation and ribosome biogenesis and suppressing autophagy. Here, we show that cytosolic pH acts as a cellular signal to activate Ras and TORC1 in response to glucose availability. We demonstrate that cytosolic pH is sensitive to the quality and quantity of the available carbon source (C-source). Interestingly, Ras/PKA and TORC1 are both activated through the vacuolar ATPase (V-ATPase), which was previously identified as a sensor for cytosolic pH in vivo. V-ATPase interacts with two distinct GTPases, Arf1 and Gtr1, which are required for Ras and TORC1 activation, respectively. Together, these data provide a molecular mechanism for how cytosolic pH links C-source availability to the activity of signaling networks promoting cell growth.

Cytosolic pH: A conserved regulator of cell growth?

Although target of rapamycin (TOR) kinase and Ras are central regulators of cell growth in yeast and mammals, the molecular mechanisms underlying their regulation by nutrients are still poorly understood. Interestingly, recent studies identified cytosolic pH as a critical regulatory signal for both pathways, which might have widespread implications for tumor cell biology.

In scarcity and abundance: metabolic signals regulating cell growth.

Although nutrient availability is a major driver of cell growth, and continuous adaptation to nutrient supply is critical for the development and survival of all organisms, the molecular mechanisms of nutrient sensing are only beginning to emerge. Here, we highlight recent advances in the field of nutrient sensing and discuss arising principles governing how metabolism might regulate growth-promoting pathways. In addition, we discuss signaling functions of metabolic enzymes not directly related to their metabolic activity.

Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism.

Predictive dynamical models are critical for the analysis of complex biological systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a computational method that incorporates all hypothetical mechanisms about the architecture of a biological system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed phosphoproteomics and imaging experiments identified a single-circuit topology with a relative probability of 99% among the 192 models. Model analysis revealed that the coupling of dynamic phenomena in Msn2 phosphorylation and transport could lead to efficient stress response signaling by establishing a rate-of-change sensor. Similar principles could apply to mammalian stress response pathways. Systematic construction of dynamic models may yield detailed insight into nonobvious molecular mechanisms.

Mass spectrometry-based metabolomics of single yeast cells.

Single-cell level measurements are necessary to characterize the intrinsic biological variability in a population of cells. In this study, we demonstrate that, with the microarrays for mass spectrometry platform, we are able to observe this variability. We monitor environmentally (2-deoxy-D-glucose) and genetically (ΔPFK2) perturbed Saccharomyces cerevisiae cells at the single-cell, few-cell, and population levels. Correlation plots between metabolites from the glycolytic pathway, as well as with the observed ATP/ADP ratio as a measure of cellular energy charge, give biological insight that is not accessible from population-level metabolomic data.

An integrated image analysis platform to quantify signal transduction in single cells.

Microscopy can provide invaluable information about biological processes at the single cell level. It remains a challenge, however, to extract quantitative information from these types of datasets. We have developed an image analysis platform named YeastQuant to simplify data extraction by offering an integrated method to turn time-lapse movies into single cell measurements. This platform is based on a database with a graphical user interface where the users can describe their experiments. The database is connected to the engineering software Matlab, which allows extracting the desired information by automatically segmenting and quantifying the microscopy images. We implemented three different segmentation methods that recognize individual cells under different conditions, and integrated image analysis protocols that allow measuring and analyzing distinct cellular readouts. To illustrate the power and versatility of YeastQuant, we investigated dynamic signal transduction processes in yeast. First, we quantified the expression of fluorescent reporters induced by osmotic stress to study noise in gene expression. Second, we analyzed the dynamic relocation of endogenous proteins from the cytoplasm to the cell nucleus, which provides a fast measure of pathway activity. These examples demonstrate that YeastQuant provides a versatile and expandable database and an experimental framework that improves image analysis and quantification of diverse microscopy-based readouts. Such dynamic single cell measurements are highly needed to establish mathematical models of signal transduction pathways.

The N-terminal domain of the V-ATPase subunit 'a' is regulated by pH in vitro and in vivo.

Regulation of the activity of vacuolar ATPase (V-ATPase) is a well known, yet poorly understood phenomenon, which might underlie the contribution of V-ATPases in various cellular signaling processes.(1) In yeast, V-ATPase is regulated by glucose and contributes to activation of cAMP-dependent protein kinase A (PKA). We have recently shown that, in vivo, glucose regulates V-ATPase through cytosolic pH, suggesting that V-ATPase contains a pH sensitive subunit, which regulates assembly of the holo-complex.(2) Here, we present the purification and biochemical characterization of the N-terminal domain of subunit 'a', Vph1N, which has been suggested to act as a pH sensor in mammalian cells.(3) Interestingly, our studies demonstrate pH-dependent oligomerization of this domain in vivo and in vitro. Moreover, we identify a membrane proximal region that is required for the pH-dependent oligomerization, and suggest a speculative model for the regulation of the V-ATPase holo-complex by pH.

Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.

Which transcription factors control the distribution of metabolic fluxes under a given condition? We address this question by systematically quantifying metabolic fluxes in 119 transcription factor deletion mutants of Saccharomyces cerevisiae under five growth conditions. While most knockouts did not affect fluxes, we identified 42 condition-dependent interactions that were mediated by a total of 23 transcription factors that control almost exclusively the cellular decision between respiration and fermentation. This relatively sparse, condition-specific network of active metabolic control contrasts with the much larger gene regulation network inferred from expression and DNA binding data. Based on protein and transcript analyses in key mutants, we identified three enzymes in the tricarboxylic acid cycle as the key targets of this transcriptional control. For the transcription factor Gcn4, we demonstrate that this control is mediated through the PKA and Snf1 signaling cascade. The discrepancy between flux response predictions, based on the known regulatory network architecture and our functional (13)C-data, demonstrates the importance of identifying and quantifying the extent to which regulatory effectors alter cellular functions.

Cytosolic pH is a second messenger for glucose and regulates the PKA pathway through V-ATPase.

Glucose is the preferred carbon source for most cell types and a major determinant of cell growth. In yeast and certain mammalian cells, glucose activates the cAMP-dependent protein kinase A (PKA), but the mechanisms of PKA activation remain unknown. Here, we identify cytosolic pH as a second messenger for glucose that mediates activation of the PKA pathway in yeast. We find that cytosolic pH is rapidly and reversibly regulated by glucose metabolism and identify the vacuolar ATPase (V-ATPase), a proton pump required for the acidification of vacuoles, as a sensor of cytosolic pH. V-ATPase assembly is regulated by cytosolic pH and is required for full activation of the PKA pathway in response to glucose, suggesting that it mediates, at least in part, the pH signal to PKA. Finally, V-ATPase is also regulated by glucose in the Min6 beta-cell line and contributes to PKA activation and insulin secretion. Thus, these data suggest a novel and potentially conserved glucose-sensing pathway and identify a mechanism how cytosolic pH can act as a signal to promote cell growth.

Recruitment of a chromatin remodelling complex by the Hog1 MAP kinase to stress genes.

For efficient transcription, RNA PolII must overcome the presence of nucleosomes. The p38-related MAPK Hog1 is an important regulator of transcription upon osmostress in yeast and thereby it is involved in initiation and elongation. However, the role of this protein kinase in elongation has remained unclear. Here, we show that during stress there is a dramatic change in the nucleosome organization of stress-responsive loci that depends on Hog1 and the RSC chromatin remodelling complex. Upon stress, the MAPK Hog1 physically interacts with RSC to direct its association with the ORF of osmo-responsive genes. In RSC mutants, PolII accumulates on stress promoters but not in coding regions. RSC mutants also display reduced stress gene expression and enhanced sensitivity to osmostress. Cell survival under acute osmostress might thus depend on a burst of transcription that in turn could occur only with efficient nucleosome eviction. Our results suggest that the selective targeting of the RSC complex by Hog1 provides the necessary mechanistic basis for this event.